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RFM Clustering of Customers using K-Means
Python notebook using data from UCI Online Retail II Data Set · 290 views · 1y ago·exploratory data analysis
Python notebook using data from UCI Online Retail II Data Set · 290 views · 1y ago·exploratory data analysis
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Input
43.51 MB
folder
Data Sources
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UCI Online Retail II Data Set
UCI Online Retail II Data Set
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calendar_view_week
online_retail_II.xlsx
online_retail_II.xlsx (43.51 MB)
calendar_view_week
Year 2009-2010
Year 2009-2010 (525k rows)
calendar_view_week
Year 2010-2011
Year 2010-2011 (542k rows)
online_retail_II.xlsx(43.51 MB)
get_app
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| Table | Total Rows | Total Columns |
|---|---|---|
| Year 2009-2010 | 525461 | 8 |
| Year 2010-2011 | 541910 | 8 |
Run Time
2.4 seconds
Timeout Exceeded
False
Output Size
0
Accelerator
None
TimeLine #Log Message
1.4s1[NbConvertApp] Converting notebook __notebook__.ipynb to html
2.3s2[NbConvertApp] Support files will be in __results___files/
2.3s3[NbConvertApp] Making directory __results___files
2.3s4[NbConvertApp] Making directory __results___files
2.3s5[NbConvertApp] Writing 306666 bytes to __results__.html
2.3s6
Complete. Exited with code 0.
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babyoda • Posted on Version 3 of 3 • 7 months ago • Options •
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6
Great application of sklearn module, i really liked that you have used the min max scaler option to avoid outliers💯
Ahmet Can KaraoğlanTopic Author • Posted on Version 3 of 3 • 7 months ago • Options •
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3
Thank you very much.
Cemal Cem Tastan • Posted on Version 3 of 3 • 7 months ago • Options •
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3
I see you really know how to find the best class model. I liked your this study which enrich your RFM clusters with K-Means !
Selen Susuz • Posted on Version 3 of 3 • 7 months ago • Options •
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2
Great Sharing👍
Sri Polu • Posted on Version 3 of 3 • 7 months ago • Options •
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2
Nice work thanks for sharing.
Marília Prata • Posted on Version 3 of 3 • 7 months ago • Options •
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2
Awesome (Recency, Frequency, Monetary - RFM) and KElbowVisualizer.
Reistatistik • Posted on Version 3 of 3 • 6 months ago • Options •
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0
Excellent job :)
Ayyuce Kaytazci • Posted on Version 3 of 3 • 7 months ago • Options •
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Thank you for sharing. Its great notebook. I will complete my own RFM project using the methods in this study. 👌